Technical Field
[0001] The present invention relates to a taxis analysis method, a cancer evaluation method,
a taxis analysis system and a program.
Background Art
[0002] In the related art, a cancer detection method using taxis of nematodes that exhibit
attraction behavior with respect to urine of a cancer patient is known (see, for example,
Non Patent Literature 1.).
Citation List
Non Patent Literature
Summary of Invention
Technical Problem
[0004] Processing of a large number of urine samples with the technique of Non Patent Literature
1 requires automation by a machine. It is conceivable to analyze taxis of nematodes
by dropping a urine sample into a culture medium in a container (for example, a Petri
dish), placing the nematodes on the culture medium, moving the sample to below an
imaging device after a predetermined time has elapsed and imaging the nematodes in
the culture medium with the imaging device. In this case, the container may rotate
in association with movement of the container. For this reason, if the container has
a point-symmetric or line-symmetric shape, there is a problem that it is not possible
to specify a place where the urine sample is dropped in the container from an image
obtained by the imaging, and it is not possible to determine whether the nematodes
exhibit attraction behavior.
[0005] The present invention has been made in view of the above problem, and it is an object
of the present invention to provide a taxis analysis method, a cancer evaluation method,
a taxis analysis system and a program capable of determining whether nematodes exhibit
attraction behavior from an image obtained by imaging even when a container on which
the nematodes are placed has a point-symmetrical or line-symmetrical shape.
Solution to Problem
[0006] A taxis analysis method according to a first aspect of the present invention, the
taxis analysis method for performing taxis analysis of nematodes using a container
in which a reference point is provided in the container or a culture medium in the
container, the taxis analysis method comprises steps of:
imaging a distribution mode of the nematodes in the container;
determining an attraction region and/or a avoidance region based on the reference
point; and
executing taxis analysis using objects of nematodes in the determined attraction region
and/or avoidance region.
[0007] According to this configuration, the attraction region and the avoidance region can
be correctly set with reference to the position of the object of the reference point
corresponding to the reference point even if the container is imaged at any rotation
angle from a position facing a bottom surface, so that it is possible to correctly
perform taxis analysis of the nematodes even if the container is imaged at any rotation
angle from the position facing the bottom surface.
[0008] A taxis analysis method according to a second aspect of the present invention, the
taxis analysis method according to the first aspect of the taxis analysis method,
wherein in the step of executing the taxis analysis, the nematodes in the determined
attraction region are counted and/or the nematodes in the determined avoidance region
are counted, and a taxis analysis result is output according to a count result.
[0009] According to this configuration, a taxis analysis result can be output even if the
container is imaged at any rotation angle from the position facing the bottom surface.
[0010] A taxis analysis method according to a third aspect of the present invention, the
taxis analysis method according to the first or the second aspect of the taxis analysis
method,
wherein the reference point is a code including container identification information
for identifying the container,
an image obtained in the step of imaging includes a code object corresponding to the
code, and
the taxis analysis method further comprises steps of:
reading the container identification information from the code object; and
storing in a storage a taxis analysis result that is a result of executing the taxis
analysis in association with the read container identification information.
[0011] According to this configuration, container identification information and the taxis
analysis result can be managed in association with each other, and thus, if a subject
and the container identification information are managed in advance in association
with each other, the subject and the taxis analysis result can be specified from the
container identification information, so that it is possible to reduce a possibility
of misidentifying the taxis analysis result of the subject.
[0012] A taxis analysis method according to a forth aspect of the present invention, the
taxis analysis method according to the third aspect of the taxis analysis method,
wherein subject identification information for identifying a subject and container
identification information are stored in the storage in association with each other,
and
the taxis analysis method further comprises a step of:
identifying subject identification information corresponding to the container identification
information read from the code object with reference to the storage.
[0013] According to this configuration, the subject can be specified from the container
identification information, so that it is possible to reduce a possibility of misidentifying
the taxis analysis result of the subject.
[0014] A taxis analysis method according to a fifth aspect of the present invention, the
taxis analysis method according to the first of the second aspect of the taxis analysis
method,
wherein the reference point includes a first reference point and/or a second reference
point.
[0015] According to this configuration, the attraction region and the avoidance region can
be determined with reference to a first reference point and/or a second reference
point.
[0016] A taxis analysis method according to a sixth aspect of the present invention, the
taxis analysis method according to any one of the first to the fifth aspect of the
taxis analysis method, further comprises a step of:
removing a lid of the container before imaging inside of the container.
[0017] According to this configuration, imaging is performed after a lid of the container
is removed, so that it is possible to grasp distribution of nematodes with high accuracy
and improve accuracy of taxis analysis.
[0018] A taxis analysis method according to a seventh aspect of the present invention, the
taxis analysis method according to any one of the first to the sixth aspect of the
taxis analysis method,
wherein in the step of determining the attraction region and/or the avoidance region,
an angle of a straight line passing through a position of an object of the reference
point and a center of an object of the container with respect to a reference line
is determined, and a reference format in which the attraction region and/or the avoidance
region is set in advance is rotated by the angle to determine the attraction region
and/or the avoidance region.
[0019] According to this configuration, it is possible to determine an appropriate attraction
region and/or avoidance region without manual operation.
[0020] A taxis analysis method according to an eighth aspect of the present invention, the
taxis analysis method according to any one of the first to the six aspect of the present
invention,
wherein in the step of determining the attraction region and/or the avoidance region,
an angle of a straight line passing through a position of an object of the reference
point and a center of an object of the container with respect to a reference line
is determined, and an image obtained by the imaging is rotated by the angle to determine
the attraction region and/or the avoidance region in the rotated image.
[0021] According to this configuration, it is possible to determine an appropriate attraction
region and/or avoidance region without manual operation.
[0022] A taxis analysis method according to a ninth aspect of the present invention, the
taxis analysis method for performing taxis analysis of nematodes using a container
in which a reference point is provided in the container or a culture medium in the
container, the taxis analysis method comprises steps of:
positioning the reference point and an imaging device in a predetermined positional
relationship;
imaging a distribution mode of the nematodes in the container by the imaging device;
determining an attraction region and/or a avoidance region; and
executing taxis analysis using objects of nematodes in the determined attraction region
and/or avoidance region.
[0023] According to this configuration, orientation and a position of the container are
always the same in an image obtained by imaging, which eliminates the need to correct
positions of the attraction region and the avoidance region in the image obtained
by imaging, so that it is possible to correctly perform taxis analysis of the nematodes.
[0024] A taxis analysis method according to a tenth aspect of the present invention, the
taxis analysis method according to any one of the first to the sixth aspect of the
taxis analysis method,
wherein in the step of determining the attraction region and/or the avoidance region,
an angle of a straight line passing through a position of an object of the reference
point and a center of an object of the container with respect to a reference line
is determined, the container is rotated by the angle, a distribution mode of the nematodes
in the container after the rotation is imaged, and the attraction region and/or the
avoidance region is determined by comparing an image obtained by the imaging with
a reference format in which the attraction region and/or the avoidance region is set
in advance.
[0025] According to this configuration, it is possible to determine an appropriate attraction
region and/or avoidance region without manual operation.
[0026] A cancer evaluation method according to an eleventh aspect of the present invention,
comprises:
the taxis analysis method according to any one of the first to the tenth aspect; and
a step of evaluating a possibility of cancer in the subject using the taxis analysis
result obtained by executing the taxis analysis.
[0027] According to this configuration, even if the container is imaged at any rotation
angle from the position facing the bottom surface, the attraction region and the avoidance
region can be correctly set on the basis of the position of the object of the reference
point corresponding to the reference point, so that even if the container is imaged
at any rotation angle from the position facing the bottom surface, it is possible
to maintain accuracy of evaluation of taxis analysis.
[0028] A taxis analysis system according to a twelfth aspect of the present invention, the
taxis analysis system for performing taxis analysis of nematodes using a container
in which a reference point is provided in the container or a culture medium in the
container, the taxis analysis system comprises:
a control unit configured to control an imaging unit to image a distribution mode
of the nematodes in the container; and
an analysis unit configured to detect a position of an object of the reference point
included in an image obtained by the imaging and corresponding to the reference point,
determine an attraction region and/or a avoidance region based on the position, and
execute taxis analysis using objects of nematodes in the determined attraction region
and/or avoidance region.
[0029] According to this configuration, the attraction region and the avoidance region can
be correctly set with reference to the position of the object of the reference point
corresponding to the reference point even if the container is imaged at any rotation
angle from a position facing a bottom surface, so that it is possible to correctly
perform taxis analysis of the nematodes even if the container is imaged at any rotation
angle from the position facing the bottom surface.
[0030] A program according to a thirteenth aspect of the present invention, the program
for performing taxis analysis of nematodes using a container in which a reference
point is provided in the container or a culture medium in the container, the program
causes a computer to be executed as:
an analysis unit configured to detect a position of an object of the reference point
corresponding to the reference point included in an image obtained by imaging a distribution
mode of the nematodes in the container, determine an attraction region and/or a avoidance
region on a basis of the position, and execute taxis analysis using objects of nematodes
in the determined attraction region and/or avoidance region.
[0031] According to this configuration, the attraction region and the avoidance region can
be correctly set with reference to the position of the object of the reference point
corresponding to the reference point even if the container is imaged at any rotation
angle from a position facing a bottom surface, so that it is possible to correctly
perform taxis analysis of the nematodes even if the container is imaged at any rotation
angle from the position facing the bottom surface.
[0032] A taxis analysis method according to a fourteenth aspect of the present invention,
the taxis analysis method for performing taxis analysis of nematodes, the taxis analysis
method comprises steps of:
imaging a distribution mode of nematodes in the container; and
executing taxis analysis using an area value of a region occupied by objects of nematodes
in an attraction region and/or a avoidance region.
[0033] A cancer evaluation method according to a fifteenth aspect of the present invention,
comprises:
the taxis analysis method according to the fourteenth adpect; and
a step of evaluating a possibility of cancer in the subject by using a taxis analysis
result obtained by executing the taxis analysis.
[0034] A taxis analysis system according to a sixteenth aspect of the present invention,
the taxis analysis system for performing taxis analysis of nematodes, the taxis analysis
system comprises:
a control unit configured to control an imaging unit to image a distribution mode
of nematodes in a container after the nematodes and a specimen of a subject are dropped
into the container; and
an analysis unit configured to execute taxis analysis using an area value of a region
occupied by objects of nematodes in an attraction region and/or a avoidance region.
[0035] A program according to a seventeenth aspect of the present invention, the program
for performing taxis analysis of nematodes, the program causes a computer to be executed
as:
an analysis unit configured to execute taxis analysis using an area value of a region
occupied by objects of nematodes in an attraction region and/or a avoidance region
included in an image obtained by imaging a distribution mode of nematodes in a container
after the nematodes and a specimen of a subject are dropped into the container.
Advantageous Effects of Invention
[0036] According to one aspect of the present invention, an attraction region and a avoidance
region can be correctly set with reference to a position of an object of a reference
point corresponding to the reference point even if a container is imaged at any rotation
angle from a position facing a bottom surface, so that taxis analysis of nematodes
can be correctly performed even if the container is imaged at any rotation angle from
the position facing the bottom surface.
Brief Description of Drawings
[0037]
Fig. 1 is a block diagram illustrating a schematic configuration of a taxis analysis
system according to the present embodiment.
Fig. 2 is an example of a schematic perspective view of a container take-out unit
13 in a state before a container is conveyed.
Fig. 3 is an example of a schematic perspective view of the container take-out unit
13 in a state after the container is conveyed.
Fig. 4 is an example of a view of a Petri dish according to the present embodiment
as viewed from above.
Fig. 5 is a flowchart illustrating an example of processing of taxis analysis according
to the present embodiment.
Fig. 6 is an example of a table of inspection information stored in a storage.
Fig. 7 is a schematic diagram of an image obtained by imaging according to the present
embodiment.
Fig. 8 is a schematic diagram illustrating an example of an attraction region and
a avoidance region in the image obtained by imaging.
Fig. 9 is a flowchart illustrating an example of a taxis analysis method according
to the present embodiment.
Fig. 10 is an example of a view of a Petri dish according to a modification as viewed
from above.
Fig. 11 is a schematic diagram of an image obtained by imaging according to the modification.
Fig. 12 is a schematic diagram illustrating an example of an attraction region and
a avoidance region in the image obtained by imaging in the modification.
Fig. 13 is an example of a reference format stored in advance in a storage 16.
Fig. 14 is a schematic diagram illustrating an example of the attraction region and
the avoidance region in the image obtained by imaging in the modification.
Fig. 15 is a schematic configuration diagram of a taxis analysis system according
to a second embodiment.
Fig. 16 is a block diagram of a taxis analysis device according to the second embodiment.
Fig. 17 is a schematic view of an image of a Petri dish on which taxis analysis is
to be performed.
Fig. 18 is a view illustrating processes of processing according to the second embodiment.
Fig. 19 is an example of a histogram of area values of objects of nematodes in the
attraction region and the avoidance region.
Fig. 20 is a flowchart illustrating an example of processing using a first method
for calculating a taxis analysis value.
Fig. 21 is an example of a histogram of the number of objects of nematodes and area
values of the objects of the nematodes in all taxis analysis regions (both the attraction
region and the avoidance region).
Fig. 22 is a flowchart illustrating an example of processing using a second method
for calculating a taxis analysis value.
Fig. 23 is a flowchart illustrating an example of processing in step S460 in Fig.
22.
Description of Embodiments
[0038] Hereinafter, embodiments will be described with reference to the drawings. However,
unnecessarily detailed description may be omitted. For example, detailed description
of well-known matters and repeated description of substantially the same configuration
may be omitted. This is to avoid unnecessary redundancy of the following description
and to facilitate understanding of those skilled in the art.
[0039] In the present embodiment, "nematodes" mean Caenorhabditis elegans. The nematode
is a popular organism that has been widely raised and studied in the world as a model
organism in biological research and has characteristics of easy breeding and excellent
olfactory sense.
[0040] In the present embodiment, "cancer" means a cancer type such as gastric cancer, colorectal
cancer, esophageal cancer, pancreatic cancer, prostate cancer, bile duct cancer, lung
cancer, blood cancer, leukemia, and lymphoma.
[0041] In the present embodiment, "taxis behavior" means attraction behavior or avoidance
behavior. The attraction behavior means behavior of reducing a physical distance from
a certain substance, and the avoidance behavior means behavior of increasing a physical
distance from a certain substance. A substance that induces attraction behavior is
referred to as an attractant, and a substance that induces avoidance behavior is referred
to as a repellent. In addition, in the present embodiment, "taxis analysis" means
analyzing taxis behavior.
[0042] In the present embodiment, a "reference point" refers to a mark (for example, printing,
patterns, and the like) or a morphological change (for example, grooves, protrusions,
and the like) provided on a container or a culture medium in order to recognize a
rotation angle of a bottom surface of the container on a plane including the bottom
surface. For example, in a case of a circular Petri dish, it is possible to distinguish
between an attraction region and a avoidance region by providing a reference point
having an asymmetric shape or providing a reference point having an arbitrary shape
at a part other than a center point of the bottom surface.
[0043] As an example, a method and a system for taxis analysis according to the present
embodiment are used to evaluate a possibility of cancer in a subject by using the
taxis behavior of nematodes as an index. However, the taxis analysis method and the
taxis analysis system according to the present embodiment can be used not only for
nematodes but also for taxis analysis of other organisms and cells, and not only for
evaluation of a possibility of cancer but also for evaluation of the possibility of
other diseases.
[0044] The container according to the present embodiment is a container having a line-symmetric
or point-symmetric shape on an inner bottom surface, and in the present embodiment,
as an example, the container is a container having a point-symmetric shape, and specifically,
will be described as a circular Petri dish. In addition, in the present embodiment,
the description will be given on the assumption that the container or the culture
medium in the container is provided with the reference point in a region other than
the point symmetry point (here, the center of the Petri dish because the container
is a circular Petri dish).
[0045] In a case where the container has a line-symmetric shape, the reference point is
provided in a region other than the symmetry axis in the container or the culture
medium in the container.
[0046] Fig. 1 is a block diagram illustrating a schematic configuration of a taxis analysis
system according to the present embodiment. As illustrated in Fig. 1, a taxis analysis
system 1 according to the present embodiment includes a processor 10, a container
supply unit 11, a stationary table 12, a container take-out unit 13, an imaging unit
15, and a storage 16.
[0047] The container supply unit 11 is a unit that conveys the container after the nematodes
and a specimen of a subject (for example, urine sample) are dropped, to the stationary
table 12. After the nematodes and the specimen of the subject are dropped, a lid is
put on the container, and the container is conveyed to the stationary table 12 in
a state where the lid is put on the container. Here, the container supply unit 11
includes a supply conveyor 111 that conveys the container to a predetermined position,
and a supply robot 112 that conveys the container from the predetermined position
to the stationary table 12.
[0048] The stationary table 12 is a table for leaving the container in a stationary manner
for a predetermined period, for example, at room temperature. During this predetermined
period, the nematodes perform attraction behavior or avoidance behavior with respect
to the specimen.
[0049] The container take-out unit 13 is a unit that takes out the container and conveys
the container to a predetermined imaging position (for example, a focal position of
the imaging unit 15). As an example, the container take-out unit 13 includes a take-out
robot 131 that takes out the container from the stationary table 12, a container conveyance
unit 132 that conveys the container to the predetermined imaging position, a lid removal
unit 133 that removes the lid of the container, and a sensor 134.
[0050] The storage 16 stores a program to be read and executed by the processor 10. The
processor 10 functions as a control unit 14 and an analysis unit 17 by reading and
executing the program stored in the storage 16.
[0051] The control unit 14 controls the container supply unit 11, the container take-out
unit 13, and the imaging unit 15.
[0052] The storage 16 also stores an image database (also referred to as an image DB) 161
and an inspection database (also referred to as an inspection DB) 162.
[0053] The imaging unit 15 images a distribution mode of the nematodes in the container
conveyed by the container take-out unit 13 and stores an image obtained by the imaging
in the image database 161 of the storage 16.
[0054] The analysis unit 17 reads the image from the image database 161 of the storage 16
and executes taxis analysis using the image obtained by imaging.
[0055] Then, the analysis unit 17 evaluates a possibility of cancer in the subject by using
a taxis analysis result obtained by executing the taxis analysis. The analysis unit
17 stores the taxis analysis result and an evaluation result of the possibility of
cancer in the subject (hereinafter, also referred to as a cancer evaluation result)
in the inspection database 162 of the storage 16 as inspection information.
[0056] Fig. 2 is an example of a schematic perspective view of the container take-out unit
13 in a state before the container is conveyed. In Fig. 2, the container conveyance
unit 132 has a robot hand 1321 that grips a Petri dish 21 which is an example of the
container. On the other hand, the lid removal unit 133 has an arm 1331 that grips
a lid 22 of the Petri dish 21.
[0057] The sensor 134 detects whether or not the robot hand 1321 of the container conveyance
unit 132 is located at a predetermined position and outputs a detection result to
the control unit 14. In a case where the sensor 134 detects whether or not the robot
hand 1321 is located at a predetermined position, the control unit 14 moves the arm
1331 of the lid removal unit 133 to the predetermined position and controls the arm
1331 to grip the lid 22 of the Petri dish 21.
[0058] As illustrated in Fig. 2, the imaging unit 15 is fixed to a support column 151,
and the support column 151 is fixed on a base member 152. A light source 153 is fixed
to the support column 151. The Petri dish 21 from which the lid 22 is removed is conveyed
immediately below the imaging unit 15 by the container conveyance unit 132.
[0059] Fig. 3 is an example of a schematic perspective view of the container take-out unit
13 in a state after the container is conveyed. As illustrated in Fig. 3, the Petri
dish 21 from which the lid 22 is removed is moved immediately below the imaging unit
15 as an example. The position of the Petri dish 21 is preferably separated by a focal
length of the imaging unit 15. In a state where the Petri dish 21 is illuminated with
light from the bottom of the Petri dish 21 by a light source 153, a distribution mode
of the nematodes in the Petri dish 21 is imaged by the imaging unit 15.
[0060] Fig. 4 is an example of a view of the Petri dish according to the present embodiment
as viewed from above. As illustrated in Fig. 4, as an example, a reference point S1
indicating positive and a reference point S2 indicating negative are provided on the
bottom surface of the Petri dish 21. In Fig. 4, as an example, the reference points
S1 and S2 are provided at point-symmetrical positions with respect to the center of
the Petri dish 21. In other words, the reference points S1 and S2 have the same distance
from the center of the Petri dish 21, and the centers of the reference points S1 and
S2 and the Petri dish 21 are on the same straight line. In addition, the reference
points S1 and S2 may be printed on the Petri dish 21 or may be expressed by providing
unevenness on the Petri dish 21. Note that a sheet on which the reference points S1
and S2 are printed may be attached to the bottom surface of the Petri dish using a
printed surface as an attachment surface.
[0061] Note that the positions of the reference points S1 and S2 in the bottom surface of
the Petri dish 21 are merely examples, and the positions are not limited thereto.
In addition, the reference points S1 and S2 may be positioned on a side surface of
the Petri dish 21 or may be provided in the culture medium.
[0062] Fig. 5 is a flowchart illustrating an example of processing of taxis analysis according
to the present embodiment.
[0063] (Step S10) First, anesthesia is dropped onto a culture medium whose horizontal position
corresponds to the positions of the reference point S1 and the reference point S2.
As a result, when nematodes reach the position of the reference point S1 or the reference
point S2 or the vicinity thereof, the nematodes cannot move due to anesthesia.
[0064] (Step S20) Next, nematodes are dropped onto the culture medium corresponding to the
substantially central position of the Petri dish 21, and a buffer is removed with
a nonwoven fabric, a dispenser, or the like.
[0065] (Step S30) Next, a urine sample derived from a cancer patient is dropped onto the
culture medium whose horizontal position corresponds to the position of the reference
point S1. As a result, when the nematodes are attracted by the smell of urine and
reach the position of the reference point S1 or the vicinity thereof, the nematodes
cannot move due to anesthesia.
[0066] Note that the order of steps S10 to S30 may be different.
[0067] (Step S40) Next, the container supply unit 11 conveys the Petri dish 21 to the stationary
table 12.
[0068] (Step S50) Next, the Petri dish 21 is left in a stationary manner on the stationary
table 12 for a predetermined period.
[0069] (Step S60) Next, the take-out robot 131 takes out the Petri dish 21 from the stationary
table 12, and the lid removal unit 133 removes the lid 22 from the Petri dish 21.
In this manner, before inside of the Petri dish 21 is imaged, the lid 22 of the Petri
dish 21 is removed.
[0070] (Step S70) Next, the container conveyance unit 132 conveys the Petri dish 21 to a
predetermined imaging position.
[0071] (Step S80) Next, the imaging unit 15 images a distribution mode of the nematodes
in the Petri dish 21.
[0072] (Step S90) Next, the analysis unit 17 executes taxis analysis.
[0073] (Step S100) Next, the analysis unit 17 evaluates a possibility of cancer in the subject
by using a taxis analysis result obtained by executing the taxis analysis. Then, the
analysis unit 17 stores the taxis analysis result and an evaluation result of the
possibility of cancer in the subject as inspection information in the inspection database
162 of the storage 16. As a result, the inspection information as illustrated in Fig.
6 is accumulated.
[0074] Fig. 6 is an example of a table of the inspection information stored in the storage.
As illustrated in Fig. 6, a table T1 accumulates records of a set of a subject ID
which is subject identification information for identifying a subject, a Petri dish
ID which is an example of container identification information for identifying a container
(here, a Petri dish as an example), a stationary start date and time, a stationary
end date and time, a temperature during stationary, an imaging ID for identifying
an image obtained by imaging, the number of attracted nematodes, the number of repelled
nematodes, a taxis index, and a cancer evaluation result. Here, the taxis index is
an example of a taxis analysis result, and the expression is, for example, the taxis
index = (the number of nematodes exhibiting attraction behavior - the number of nematodes
exhibiting avoidance behavior)/the total number of nematodes.
[0075] Fig. 7 is a schematic diagram of an image obtained by imaging according to the present
embodiment. As illustrated in Fig. 7, an object OB3 of the Petri dish 21, an object
OB1 of the reference point S1, and an object OB2 of the reference point S2 are illustrated
in the image obtained by imaging.
[0076] Fig. 8 is a schematic diagram illustrating an example of the attraction region and
the avoidance region in an image obtained by imaging. As illustrated in Fig. 8, in
an image obtained by imaging G1b, a center P1 of the object OB3 of the Petri dish
21 is extracted as a point at which two straight lines that are orthogonal to tangents
of a contour of the object OB3 of the Petri dish 21 and that are drawn from two different
positions on the contour, intersect each other. A straight line L1 orthogonal to the
straight line L0 can be drawn at a position close to the object OB1 by a distance
d1 from the center P1 along the straight line L0 connecting the center P1 of the object
OB3 of the Petri dish 21 and the object OB1 of the reference point S1. In the straight
line L0, a straight line L2 orthogonal to the straight line L0 can be drawn at a position
away from the object OB1 by the distance d1 from the center P1. A region R1 surrounded
by the straight line L1 and the contour of the object OB3 of the Petri dish 21 is
an attraction region. A region R2 surrounded by the straight line L2 and the contour
of the object OB3 of the Petri dish 21 is a avoidance region.
[0077] In a case of the example of Fig. 8, as a method of determining the attraction region,
for example, the analysis unit 17 extracts the center P1 of the object OB3 of the
Petri dish 21 from the image obtained by imaging G1b. Furthermore, the analysis unit
17 detects a position of the object OB1 at the reference point S1 from the image obtained
by imaging G1b, for example. For example, the analysis unit 17 sets the straight line
L1 orthogonal to the straight line L0 at a position close to the object OB1 by the
distance d1 from the center P1 along the straight line L0 connecting the center P1
of the object OB3 of the Petri dish 21 and the object OB1 of the reference point S1
and determines the region R1 surrounded by the straight line L1 and the contour of
the object OB3 of the Petri dish 21 as the attraction region. In addition, as a method
of determining the avoidance region, in a case of the example of Fig. 8, the straight
line L2 orthogonal to the straight line L0 is set at a position away from the object
OB1 by the distance d1 from the center P1 along the straight line L0, and the region
R2 surrounded by the straight line L2 and the contour of the object OB3 of the Petri
dish 21 is determined as the avoidance region.
[0078] Note that the analysis unit 17 does not have to extract the center P1 of the object
OB3 of the Petri dish 21 from the image obtained by imaging G1b. In a case where the
reference point S1 and the reference point S2 are at point-symmetrical positions with
respect to the center of the Petri dish 21, the analysis unit 17 may extract the object
OB1 of the reference point S1 and the object OB2 of the reference point S2 from the
image obtained by imaging G1b and may set a straight line passing through the center
of the object OB1 of the reference point S1 and the center of the object OB2 of the
reference point S2 as the straight line L0.
[0079] As described above, the analysis unit 17 reads the image from the image database
161 of the storage 16, detects the position of an object of the reference point (for
example, object OB1 at reference point S1 in Figs. 7 and 8) corresponding to the reference
point included in the image obtained by imaging and determines the attraction region
(for example, the region R1 in Fig. 8) and the avoidance region (for example, the
region R2 in Fig. 8) on the basis of the position. Then, the analysis unit 17 performs
taxis analysis using the objects of the nematodes in the determined attraction region
and avoidance region.
[0080] In this event, the analysis unit 17 determines the number of objects of the nematodes
in the attraction region as the number of nematodes exhibiting the attraction behavior.
In addition, the analysis unit 17 determines the number of objects of the nematodes
in the avoidance region as the number of nematodes exhibiting the avoidance behavior.
[0081] Next, a specific example of the taxis analysis processing in step S90 in Fig. 5 will
be described with reference to Fig. 9. Fig. 9 is a flowchart illustrating an example
of a taxis analysis method according to the present embodiment.
[0082] (Step S110) First, the analysis unit 17 of the processor 10 acquires image data from
the image DB 161.
[0083] (Step S120) Next, the analysis unit 17 detects a position of the Petri dish in the
image data.
[0084] (Step S130) Next, the analysis unit 17 detects a reference point of the Petri dish
in the image data. For example, in a case where the image data is Fig. 8, the analysis
unit 17 detects the object OB1 at the reference point S1 and/or the object OB2 at
the reference point S2 from the image data G1b.
[0085] (Step S140) Next, the analysis unit 17 sets a nematode taxis analysis region in
accordance with the reference point of the petri dish. In this event, for example,
in a case where the image data is Fig. 8, the analysis unit 17 determines the region
R1 in Fig. 8 as the attraction region and determines the region R2 in Fig. 8 as the
avoidance region on the basis of the object OB1 at the reference point S1 and/or the
object OB2 at the reference point S2.
[0086] (Step S150) Next, the analysis unit 17 performs image analysis for each analysis
region determined in step S140. In this event, for example, the analysis unit 17 executes
image processing for emphasizing contours of the nematodes in the image data.
[0087] (Step S160) Next, the analysis unit 17 counts the nematodes for each analysis region.
In this event, for example, the analysis unit 17 counts regions of nematodes in the
image data for each analysis region.
[0088] (Step S170) Next, the analysis unit 17 performs taxis analysis from the count value
of the nematodes for each analysis region. In this event, for example, the analysis
unit 17 calculates the taxis index. In this way, the nematodes in the determined attraction
region are counted, the nematodes in the determined avoidance region are counted,
and the taxis analysis result is output in accordance with the count results.
[0089] As described above, the taxis analysis method according to the present embodiment
is a taxis analysis method for performing taxis analysis of nematodes using a container
in which a reference point is provided in a region other than a symmetry axis or a
region other than a symmetry point in the container or a culture medium in the container.
This taxis analysis method includes steps of: imaging a distribution mode of the nematodes
in the container after the nematodes and a specimen of the subject are dropped into
the container; detecting a position of an object of the reference point corresponding
to the reference point included in an image obtained by the imaging; determining an
attraction region and a avoidance region on the basis of the position; and performing
taxis analysis using objects of nematodes in the determined attraction region and
avoidance region.
[0090] With this configuration, the attraction region and the avoidance region can be correctly
set with reference to the position of the object of the reference point corresponding
to the reference point even if the container is imaged at any rotation angle from
the position facing the bottom surface, so that the taxis analysis of the nematodes
can correctly be performed even if the container is imaged at any rotation angle from
the position facing the bottom surface.
[0091] Note that step S130 can be omitted in Fig. 9. In this case, the container or the
camera may be positioned such that the reference point of the container and the camera
have a predetermined positional relationship at the imaging position in step S70 in
Fig. 5. With this configuration, the orientation and the position of the container
are always the same in the image obtained by imaging, which eliminates the need to
correct the positions of the attraction region and the avoidance region from the image
obtained by imaging, so that it is possible to correctly perform taxis analysis of
the nematodes.
[0092] In addition, in the present embodiment, the analysis unit 17 evaluates a possibility
of cancer in the subject by applying the taxis analysis result obtained by executing
the taxis analysis to a predetermined evaluation rule. For example, in a case where
the evaluation rule evaluates a possibility of cancer on the basis of whether or not
the result is higher or lower than a threshold, the analysis unit 17 may evaluate
that the possibility of cancer is high when the taxis analysis result is higher than
the threshold and may evaluate that the possibility of cancer is low when the taxis
analysis result is equal to or lower than the threshold. As a result, accuracy of
evaluation of the possibility of cancer can be maintained regardless of the rotation
angle at which the container is imaged from the position facing the bottom surface.
[0093] In the present embodiment, the positive and negative reference points are provided
on the bottom surface of the Petri dish, but the present invention is not limited
thereto, and the reference point may be provided on a side surface of the Petri dish,
or the reference point may be provided on the culture medium.
<Modification>
[0094] Note that in the present embodiment, the positive and negative reference points are
attached to the Petri dish, but the reference point is not limited thereto. The reference
point may be a code (for example, a two-dimensional code) including container identification
information for identifying the container.
[0095] Fig. 10 is an example of a view of a Petri dish according to a modification as viewed
from above. As illustrated in Fig. 10, a two-dimensional code S3 is provided on a
bottom surface of a Petri dish 21b. For example, the two-dimensional code may be printed
on the Petri dish 21b or may be expressed by providing unevenness on the Petri dish
21b. Note that paper on which the two-dimensional code is printed may be attached
to the bottom surface of the Petri dish 21b with a printing surface as an attachment
surface.
[0096] Fig. 11 is a schematic diagram of an image obtained by imaging according to the modification.
As illustrated in Fig. 11, in an image obtained by imaging G2, a code object OB11
corresponding to the two-dimensional code S3 is included in an object OB12 corresponding
to the Petri dish. As described above, the image obtained by imaging includes the
code object corresponding to the code.
[0097] In this case, the analysis unit 17 reads the container identification information
(here, the Petri dish ID as an example) from the code object OB11. Then, the analysis
unit 17 stores a taxis analysis result which is a result of performing taxis analysis
in the storage 16 in association with the read container identification information
(here, Petri dish ID as an example).
[0098] With this configuration, the container identification information and the taxis analysis
result can be managed in association with each other, and thus, if the subject identification
information and the container identification information are managed in advance in
association with each other, it is possible to specify the taxis analysis result of
the subject and the taxis analysis result from the container identification information,
so that it is possible to reduce the possibility of misidentifying a taxis analysis
result of the subject.
[0099] When an urine specimen is dropped into a container (here, a Petri dish as an example),
a combination of the subject of the urine specimen and the container is determined,
and thus, in this event, subject identification information for identifying the subject
and the container identification information may be stored in the storage 16 in association
with each other to manage the subject and the container identification information
in association with each other. In this case, the analysis unit 17 may specify the
subject identification information corresponding to the container identification information
read from the code object with reference to the storage 16. With this configuration,
the subject can be specified from the container identification information, so that
it is possible to reduce the possibility of misidentifying the taxis analysis result
of the subject.
[0100] Similarly, the analysis unit 17 may output a set of subject identification information
and a taxis analysis result or a set of subject identification information and a cancer
evaluation result corresponding to the container identification information read from
the code object with reference to the storage 16. With this configuration, the taxis
analysis result or the cancer evaluation result for each subject can be obtained,
so that it is possible to reduce the possibility of misidentifying the taxis analysis
result or the cancer evaluation result of the subject.
[0101] As described above, the taxis analysis system according to the present embodiment
is a taxis analysis system that performs taxis analysis of nematodes using the container
or the container in which the reference point is provided in the culture medium. A
taxis analysis system according to the present embodiment includes: a control unit
configured to control an imaging unit to image a distribution mode of nematodes in
a container after the nematodes and a specimen of a subject are dropped into the container;
and an analysis unit configured to detect a position of an object of the reference
point corresponding to the reference point included in the image obtained by the imaging,
determine an attraction region and a avoidance region on the basis of the position,
and execute taxis analysis using objects of the nematodes in the determined attraction
region and avoidance region.
[0102] With this configuration, the attraction region and the avoidance region can be correctly
set with reference to the position of the object of the reference point corresponding
to the reference point even if the container is imaged at any rotation angle from
the position facing the bottom surface, so that the taxis analysis of the nematodes
can correctly be performed even if the container is imaged at any rotation angle from
the position facing the bottom surface.
[0103] Fig. 12 is a schematic diagram illustrating an example of the attraction region and
the avoidance region in the image obtained by imaging in the modification. As illustrated
in Fig. 12, in a straight line L10 connecting the center P2 of the object OB12 of
the Petri dish 21 and the code object OB11 of the two-dimensional code, a straight
line L11 orthogonal to the straight line L10 can be drawn at a position close to the
code object OB11 by a distance d1 from the center P2. Furthermore, in the straight
line L10, a straight line L12 orthogonal to the straight line L10 can be drawn at
a position away from the code object OB11 by the distance d1 from the center P2. A
region R3 surrounded by the straight line L11 and the contour of the object OB12 of
the Petri dish 21 is an attraction region. A region R4 surrounded by the straight
line L12 and the contour of the object OB12 of the Petri dish 21 is a avoidance region.
[0104] In this case, the analysis unit 17 may read the image from the image database 161
of the storage 16, detect the position of the code object (for example, the code object
OB11 of Fig. 12) corresponding to the two-dimensional code included in the image obtained
by imaging, determine the attraction region (for example, the region R3 in Fig. 12)
and the avoidance region (for example, the region R4 in Fig. 12) on the basis of the
position and execute taxis analysis using objects of the nematodes in the determined
attraction region and avoidance region. Note that the code is not limited to the two-dimensional
code and may be a barcode.
[0105] Fig. 13 is an example of a reference format stored in advance in the storage 16.
As illustrated in Fig. 13, the reference format is a format serving as a reference
for setting the attraction region and the avoidance region. In the reference format
in Fig. 13, the straight line L10 passing through the center of the circle C1 and
separated in parallel by a distance d in a -x direction with respect to a straight
line L15 that is parallel to a y axis is illustrated. A region R5 defined by the straight
line L15 and the circle C1 is a reference attraction region. Similarly, in the reference
format in Fig. 13, the straight line L10 passing through the center of the circle
C1 and separated in parallel in a +x direction by a distance d with respect to a straight
line L16 that is parallel to the y axis is illustrated. A region R6 defined by the
straight line L16 and the circle C1 is a reference avoidance region.
[0106] An example of processing in step S140 in Fig. 9 will be described with reference
to Fig. 14. Fig. 14 is a schematic diagram illustrating an example of the attraction
region and the avoidance region in the image obtained by imaging in the modification.
The analysis unit 17 recognizes the Petri dish object OB12 by image processing and
recognizes the center P2 of the Petri dish object OB12. Next, the analysis unit 17
recognizes a two-dimensional code, which is an example of the reference point, by
image processing. Note that the order of the recognition processing of the center
P2 and the recognition processing of the two-dimensional code may be reversed.
[0107] (Step S230) Next, the analysis unit 17 determines a straight line L12 (straight line
L12 illustrated in Fig. 14) connecting the center P2 and the two-dimensional code.
[0108] (Step S240) Next, the analysis unit 17 obtains an angle θ (angle θ illustrated in
Fig. 14) formed by the straight line L11 and the straight line L12 parallel to a longitudinal
direction of the image G2 which is an example of the reference line.
[0109] Next, steps S251 and S252 are executed, or step S261 is executed.
(Step S251) As illustrated in Fig. 14, the analysis unit 17 rotates the reference
format of Fig. 13 counterclockwise by θ about the center of the circle.
(Step S252) Next, as illustrated in Fig. 14, the analysis unit 17 superimposes the
reference format after counterclockwise rotation by θ so that the center of the circle
C1 of the reference format after counterclockwise rotation θ overlaps the center P2
of the Petri dish object OB12 in the image G2 or a case where the reference format
is superimposed is assumed. Then, the analysis unit 17 sets the region R5 of the reference
format after superimposition (or in a case where it is assumed that the reference
format is superimposed) as the attraction region and sets the region R6 of the reference
format after superimposition (or in a case where the reference format is superimposed)
as the avoidance region.
[0110] Note that, at the time of superimposition, in a case where the circle C1 in the reference
format does not match an outer periphery (that is, the contour) of the Petri dish
object OB12 in the image G2, the analysis unit 17 may enlarge or reduce the circle
C1 in the reference format so that the circle C1 in the reference format matches the
outer periphery of the Petri dish object OB12 in the image G2. In this case, the analysis
unit 17 sets a region R5 of the enlarged or reduced reference format as the attraction
region and sets a region R6 of the enlarged or reduced reference format as the avoidance
region.
[0111] (Step S261) The analysis unit 17 rotates the image G2 clockwise by θ. Next, the analysis
unit 17 sets the region R5 between the straight line L15 parallel to the straight
line L10 separated from the straight line L10 by the distance d1 and the contour of
the object OB12 as the attraction region and sets the region R6 between the straight
line L16 parallel to the straight line L10 separated from the straight line L10 by
the distance d1 and the contour of the object OB12 as the avoidance region.
[0112] Note that, in step S261, the image G2 is rotated clockwise by θ, but the present
invention is not limited thereto, and the robot hand 1321 may include a mechanism
for holding and rotating the Petri dish, and the robot hand 1321 may physically rotate
the Petri dish itself clockwise by θ while holding the Petri dish. In this case, the
attraction region and/or the avoidance region may be determined by imaging the distribution
mode of the nematodes in the container after the rotation and comparing an image obtained
by the imaging with the reference format in which the attraction region and/or the
avoidance region is set in advance. Note that, here, a modification in which the robot
hand 1321 grips and rotates the Petri dish has been described, but the present invention
is not limited thereto, and the Petri dish may be placed on a table (for example,
a mortar base) provided with a recess on a surface and may be physically rotated by
the robot hand 1321 in a state where the Petri dish is placed.
[0113] In the present embodiment, both the attraction region and the avoidance region are
set, the number of nematodes in both regions is counted, and the taxis analysis is
performed using the number of nematodes in both regions, but the invention is not
limited thereto. The distribution of nematodes after left in a stationary manner tends
to concentrate at a location where anesthesia is dropped to the culture medium. Thus,
only one of the attraction region and the avoidance region may be set, the number
of nematodes in the set region may be counted, and taxis analysis may be performed
using the number of nematodes in the set region and the number of nematodes in the
region of the Petri dish object OB12. For example, in a case where the attraction
region is set, the number of nematodes in the avoidance region can be regarded as
a value obtained by subtracting the number of nematodes in the attraction region from
the number of nematodes in the region of the Petri dish object OB12 corresponding
to an inner bottom surface of the Petri dish.
[0114] Note that in the present embodiment, the taxis analysis method illustrated in Fig.
9 is performed in order to evaluate the possibility of cancer in the subject, but
the taxis analysis method is not limited to cancer evaluation and may be performed
in a case where taxis of other organisms or cells is evaluated.
<Second Embodiment>
[0115] Next, a second embodiment will be described. A taxis index in related art is obtained
by counting the number of nematodes by visual observation under a microscope. Specifically,
the taxis action of nematodes has been evaluated using a taxis analysis value as an
index, and a taxis index calculated from the following expression has been used.

[0116] Here, x is the number of nematodes that have exhibited attraction behavior with respect
to the sample, and y is the number of nematodes that have exhibited avoidance behavior
with respect to the sample, and this taxis index is the same as that of the first
embodiment.
[0117] As a method of automatically calculating this taxis index, the following calculation
method can be considered. In other words, when a camera is disposed from above the
Petri dish on which the nematodes are placed and the Petri dish is irradiated by a
light source from below the Petri dish, imaging is performed at higher luminance than
the surroundings due to diffuse reflection of light generated by the nematodes, so
that the region of the nematodes is identified. Then, there is a method in which calculation
is performed by the following method using the image or moving image obtained by imaging.
[0118]
- (1) A method in which a taxis index is calculated by measuring a center of gravity
of luminance of a predetermined region in the image obtained by imaging.
- (2) A method in which the number of nematode regions is counted in a predetermined
region in the image obtained by imaging.
[0119] In the case of (1) and (2), the number of regions having higher luminance than the
surroundings is counted as the number of nematodes. However, if a plurality of nematodes
are imaged in an overlapping state, the nematodes are recognized as one region, and
the actual number of nematodes may be greatly different from the number of regions.
For this reason, in a case where a computer automatically counts nematodes from an
image, in a case where nematodes overlap in the image, it is difficult to accurately
count the number of nematodes from the image, and there is a problem that the taxis
index calculated by the computer is greatly different from the taxis index calculated
by visually counting the nematodes by a human (hereinafter, referred to as a taxis
index calculated by manual counting).
[0120] In addition, if a fixed threshold is set for regions to be counted, there is also
a problem that accuracy of the taxis analysis value may decrease due to a difference
in imaging conditions.
[0121] On the other hand, in the present embodiment, a method for determining a new taxis
analysis value has been developed in order to automatically determine whether or not
there is cancer from the image obtained by imaging the nematodes by a computer. In
the present embodiment, the computer calculates the taxis index using the method for
calculating a new taxis analysis value and automatically evaluates a possibility of
cancer in the subject using the new taxis analysis value.
[0122] According to this, even in a case where the nematodes overlap in the image, the taxis
analysis value calculated by the method for calculating the new taxis analysis value
becomes a value close to "the taxis index calculated by manual counting", so that
the computer can automatically determine a possibility of cancer in the subject from
the image with accuracy equivalent to "the taxis index calculated by manual counting".
[0123] In addition, although an area of the objects corresponding to the nematodes relatively
changes depending on the imaging conditions, according to the method for calculating
a taxis analysis value according to the present embodiment, even if the imaging conditions
change, a result is obtained in which a difference between the taxis analysis value
calculated by the method for calculating the new taxis analysis value and the taxis
index calculated by manually counting is small. Thus, in the present embodiment, the
computer can automatically determine a possibility of cancer in the subject from the
image with accuracy equivalent to that of "the taxis index calculated by manually
counting" without being greatly affected by the imaging conditions.
<System Configuration>
[0124] Fig. 15 is a schematic configuration diagram of a taxis analysis system according
to the second embodiment. A taxis analysis system 1b includes a light source 21, a
camera 15b which is an example of an imaging unit, a taxis analysis device 3 which
is connected to the camera 15b and a storage 16 which stores an image database (image
DB) 161. The imaging unit 15 is disposed above the Petri dish 21 while light of the
light source 21 is radiated from below the Petri dish 21 after the taxis test, and
the taxis analysis device 3 images the Petri dish 21 to calculate a taxis analysis
value. The light source 21 is desirably a circular white LED. The camera 15b is controlled
by the taxis analysis device 3, and the image obtained by imaging by the camera 15b
is accumulated in the image database 161.
[0125] Fig. 16 is a block diagram of the taxis analysis device according to the second embodiment.
As illustrated in Fig. 16, the taxis analysis device 3 according to the second embodiment
includes a processor 10b, and the processor 10b functions as a camera control unit
31, an image processing unit 32, and an analysis unit 33 by reading and executing
a program stored in the storage 16. The camera control unit 31 controls the camera
15b to image the Petri dish 21 and stores an image obtained by imaging in the image
database 161 of the storage 16. The image processing unit 32 performs image processing.
The analysis unit 33 calculates a taxis analysis value using the image after the image
processing and evaluates a possibility of cancer using the taxis analysis value.
<Objects of Nematodes and Area Value>
[0126] Fig. 17 is a schematic view of an image of the Petri dish on which taxis analysis
is to be performed. As illustrated in Fig. 17, an attraction region R11 in which it
is determined that the nematodes exhibit the attraction behavior and a avoidance region
R12 in which it is determined that the nematodes exhibit the avoidance behavior are
illustrated. Fig. 18 is a diagram illustrating processes of processing according to
the second embodiment. Hereinafter, the processes of the processing will be described
with reference to Fig. 18.
[0127] The image processing unit 32 extracts regions occupied by objects of nematodes corresponding
to the respective nematodes in each of the attraction region (also referred to as
a positive region) and the avoidance region (also referred to as a negative region)
illustrated in Fig. 17 by image processing (for example, edge extraction by hue, binarization
processing, or the like) from the image obtained by imaging. Then, the analysis unit
33 calculates an area of the extracted objects of nematodes. Specifically, for example,
the analysis unit 33 counts the number of pixels occupied by the objects of nematodes.
[0128] There are two types of methods for calculating the taxis analysis value of the present
embodiment, and in both methods, the taxis analysis value is calculated using the
area value of the objects of nematodes. Each will be described below.
<First Calculation Method >
[0129] First, a first calculation method of the taxis analysis value of the present embodiment
will be described. The first calculation method is a method in which the taxis analysis
value is calculated using a sum of area values of objects of nematodes in the attraction
region and a sum of area values of objects of nematodes in the avoidance region.
[0130] Fig. 19 is an example of a histogram of area values of the objects of nematodes in
the attraction region and the avoidance region. In the taxis test, adult worms having
substantially the same size are used as the nematodes, but the area value of an object
of each nematode varies due to light diffusely reflected by the nematodes at the time
of imaging. (1) Regarding this variation, it is observed that variations in area values
of the attraction region and the avoidance region are substantially the same. From
this, even if the taxis analysis value was calculated using the following expression,
the taxis analysis value was less different from the taxis index calculated by manual
counting.

[0131] Here, I is the taxis analysis value, S
A is a sum of the area values of the objects of nematodes in the attraction region,
and S
B is a sum of the area values of the objects of the nematodes in the avoidance region.
The above expression (1) is used to calculate the taxis analysis value in the flowchart
of Fig. 20 which will be described later. Note that only one of the attraction region
and the avoidance region may be set, and the area value of the objects of the nematodes
in the set region and the area value of the objects of the nematodes in the entire
region of the Petri dish object OB12 may be used to perform taxis analysis. For example,
in a case where the attraction region is set, the area value of the objects of the
nematodes in the avoidance region can be regarded as a value obtained by subtracting
the area value of the objects of the nematodes in the attraction region from the area
value of the objects of the nematodes in the entire region of the Petri dish object
OB12 corresponding to the inner bottom surface of the Petri dish.
[0132] In addition, (1) no deviation in chemotaxis action depending on the size of the adult
nematodes used for the test is observed even when there are individual differences
in the size of the adult nematodes, (2) in most tests, in distribution of the nematodes
after the test, a state where one nematode is in a stationary state is more often
seen than a state where a plurality of nematodes overlap each other, (3) even if a
result of a small absolute value of the taxis analysis value is obtained in a cancer
test, states where a plurality of nematodes overlap each other tend not to be unevenly
distributed in each of the attraction region (+) and the avoidance region (-), and
(4) particularly, a result comparable to a clinical result obtained by the method
in related art in a cancer test is obtained, and thus, even in a case where the nematodes
are imaged in a state where a plurality of nematodes overlap each other, the "taxis
analysis value calculated by the calculation of the above expression (1) by the computer"
does not deviate from the "taxis index calculated by manual counting".
[0133] Fig. 20 is a flowchart illustrating an example of processing using the first calculation
method of the taxis analysis value.
[0134] (Step S310) First, the camera control unit 31 controls the camera 15b to image the
Petri dish 21 containing nematodes and stores image data obtained by the imaging in
the storage 16. The image processing unit 32 acquires the image data.
[0135] (Step S320) Next, the image processing unit 32 detects the position of the Petri
dish in the image data.
[0136] (Step S330) Next, the image processing unit 32 detects a reference point of the
Petri dish in the image data.
[0137] (Step S340) Next, the image processing unit 32 sets the attraction region and the
avoidance region of the nematodes in accordance with the reference point of the Petri
dish. Here, the attraction region and the avoidance region are collectively referred
to as a taxis analysis region.
[0138] (Step S350) Next, the analysis unit 33 determines an area value of an area occupied
by an object of each nematode corresponding to each nematode (object of the nematode)
for each attraction region and each avoidance region.
[0139] (Step S360) Next, the analysis unit 33 calculates a sum S
A of the area values of the objects of the nematodes in the attraction region and a
sum S
B of the area values of the objects of the nematodes in the avoidance region and substitutes
the calculated sum S
A and the sum S
B into expression (1) to calculate the taxis analysis value according to expression
(1).
<Second Calculation Method>
[0140] Next, a second calculation method of the taxis analysis value of the present embodiment
will be described. The second calculation method is a method in which the taxis analysis
value is calculated using a peak in a histogram of area values of the objects of the
nematodes.
[0141] Fig. 21 is an example of a histogram of the number of objects of nematodes and area
values of the objects of the nematodes in all the taxis analysis regions (both the
attraction region and the avoidance region). Fig. 21 illustrates a histogram W3 of
the number of objects of the nematodes and area values of the objects of the nematodes
in all the taxis analysis regions (both the attraction region and the avoidance region).
In Fig. 21, an area range U1 of one nematode represents an area range of one nematode
and is a range between a boundary line L21 and a boundary line L22. In addition, an
area range U2 of two nematodes represents an area range in a case where two nematodes
overlap and is a range between the boundary line L22 and a boundary line L23. In addition,
an area range U3 of three nematodes represents an area range in a case where three
nematodes overlap and is a range between the boundary line L23 and a boundary line
L24.
[0142] It has been observed that an area value of a region where a plurality of nematodes
overlap is larger than that of an object of one nematode, and a possible range of
the area value varies for each number of overlapping nematodes. In the second calculation
method, as illustrated in Fig. 21, for each of the regions R21, R22, and R23 including
one maximum point, the area range (for example, the area range U1 in a case of one
nematode, the area range U2 in a case of two nematode, and the area range U3 in a
case of three nematodes) of the region occupied for each number of nematodes is set
from the histogram of the number of objects of the nematodes and the area value of
the objects of the nematodes as illustrated in Fig. 21. The number of objects of the
nematodes is integrated for each set area range, and the taxis analysis value is calculated
according to the following equation (2).

[0143] Here, I is a taxis analysis value, N
A is a sum of "the number of nematodes assigned to the area range" × "the number of
objects of the nematodes falling within the area range" in the attraction region,
and N
B is a sum of "the number of nematodes assigned to the area range" × "the number of
objects of the nematodes falling within the area range" in the avoidance region. Note
that only one of the attraction region and the avoidance region may be set, and the
area value of the objects of the nematodes in the set region and the area value of
the objects of the nematodes in the entire region of the Petri dish object OB12 may
be used to perform taxis analysis. For example, in a case where the attraction region
is set, the N
B in the avoidance region can be regarded as a value obtained by subtracting the N
A in the attraction region from the sum of "the number of nematodes assigned to the
area range" × "the number of objects of the nematodes falling within the area range"
in the entire region of the Petri dish object OB12.
[0144] In the second calculation method, (1) it has been observed that the distribution
of the nematodes after the test is most in a state where one nematode is in a stationary
state, and the number of states tends to be smaller in a state where a plurality of
nematodes overlap each other as the number of overlaps increases, and (2) from the
histogram of the area values of the objects of the nematodes in the attraction region
(+) and the avoidance region (-), the overlapping state of one nematode, two nematodes,
and three nematodes ... can be predicted from a maximum point and a minimum point
of the histogram. Thus, even in a case where the images of the nematodes overlap each
other, the "taxis analysis value calculated by automatic calculation by the computer"
does not deviate from the "taxis index calculated by manual counting".
[0145] Fig. 22 is a flowchart illustrating an example of processing using the second calculation
method of the taxis analysis value.
[0146] (Step S410) First, the camera control unit 31 controls the camera 15b to image the
Petri dish 21 containing nematodes and stores image data obtained by the imaging in
the storage 16. The image processing unit 32 acquires the image data.
[0147] (Step S420) Next, the image processing unit 32 detects the position of the Petri
dish in the image data.
[0148] (Step S430) Next, the image processing unit 32 detects a reference point of the Petri
dish in the image data.
[0149] (Step S440) Next, the image processing unit 32 sets the attraction region and the
avoidance region of the nematodes in accordance with the reference point of the Petri
dish.
[0150] (Step S450) Next, the analysis unit 33 determines the area value of the area occupied
by each object of the nematode corresponding to each nematode for each attraction
region and each avoidance region.
[0151] (Step S460) Next, the analysis unit 33 uses a histogram of the number of objects
of the nematodes and the area value in the entire taxis analysis region (see Fig.
21) to determine the range of the area of the region occupied by each number of nematodes.
Details of this processing will be described later with reference to Fig. 23.
[0152] (Step S470) Next, in each of the area ranges U1, U2, and U3 of the taxis analysis
region (that is, each of the attraction region and the avoidance region), the number
of objects of the nematodes falling within the area range is multiplied by the number
of nematodes assigned to the area range, the sum of the multiplied values is calculated
for each of the taxis analysis regions (that is, for each of the attraction region
and the avoidance region), and the taxis analysis value is determined according to
expression (2) using the sums N
A and N
B for each of the taxis analysis regions.
[0153] Fig. 23 is a flowchart illustrating an example of processing in step S460 of Fig.
22.
[0154] (Step S510) First, the analysis unit 33 obtains a maximum point and a minimum point
of the histogram (see Fig. 21) of the number of objects of the nematodes and the area
value in the entire taxis analysis region. Then, the index n is set to 1.
[0155] (Step S520) Next, the analysis unit 33 determines whether or not there is an n-th
minimum point from the left.
[0156] (Step S530) In a case where it is determined in step S520 that there is the n-th
minimum point from the left (step S520: Yes), the analysis unit 33 sets a lower limit
of the area range of one nematode to a predetermined value when n = 1. Here, the predetermined
value is a value set for exclusion as noise of a small nematode that is not an adult,
dust, or the like.
[0157] When n is equal to or greater than 2, the analysis unit 33 sets the lower limit of
the area range of n nematodes to the x coordinate + 1 at the (n-1)-th minimum point
from the left of the histogram.
[0158] When n = 1, assuming that Xmax1 is the x coordinate at the first maximum point from
the left, the lower limit of the area value of one nematode may be set to Xmax1 -
(half width at half maximum of the first maximum point from the left) .
[0159] (Step S540) The analysis unit 33 sets the x coordinate at the n-th minimum point
from the left of the histogram as the upper limit of the area range of n nematodes.
Then, the analysis unit 33 increases the index n by 1 and repeats the processing of
step S520 and subsequent steps.
[0160] (Step S550) In a case where it is determined in step S520 that there is no n-th minimum
point from the left (step S520: No), it is determined whether or not the upper limit
of the area range of (n -1) nematodes is equal to or greater than the predetermined
value.
[0161] (Step S560) In a case where the upper limit of the area range of (n -1) nematodes
is equal to or greater than the predetermined value in step S550 (step S550: Yes),
the analysis unit 33 does not set the upper limit of the area range of n nematodes
(that is, the upper limit of the area range of n nematodes becomes equal to or greater
than the lower limit of the area range of n nematodes). Note that the present invention
is not limited thereto, and assuming that the x coordinate of the n-th maximum point
is Xmaxn, the analysis unit 33 may set the upper limit of the area range of n nematodes
to Xmaxn + (half width at half maximum of the n-th maximum point from the left).
[0162] (Step S570) In a case where the upper limit of the area range of (n -1) nematodes
is not equal to or greater than the predetermined value in step S550, that is, less
than the predetermined value (step S550: No), the analysis unit 33 sets the upper
limit of the area range of n nematodes to the predetermined value.
[0163] Note that at least part of the control unit 14 and the analysis unit 17 described
in the above-described embodiments may be configured by hardware or software. A program
for implementing at least part of the functions of the analysis unit 17 may be stored
in a recording medium such as a flexible disk and a CD-ROM and may be read and executed
by a computer. The recording medium is not limited to a removable recording medium
such as a magnetic disk and an optical disk and may be a fixed recording medium such
as a hard disk device or a memory.
[0164] In addition, a program that implements at least part of the functions of the control
unit 14 and the analysis unit 17 may be distributed via a communication line (including
wireless communication) such as the Internet. Further, the program may be distributed
via a wired line or a wireless line such as the Internet or stored in a recording
medium in an encrypted, modulated, or compressed state.
[0165] Furthermore, the control unit 14 and the analysis unit 17 may be caused to function
by one or a plurality of information processing devices. In a case of using a plurality
of information processing devices, one of the information processing devices may be
a computer, and the function may be implemented as at least one unit of the analysis
unit 17 by the computer executing a predetermined program.
[0166] In the invention of the method, all the processes (steps) may be implemented by automatic
control by a computer. In addition, each process may be implemented by a computer
while progress of the processes is manually controlled. Furthermore, at least part
of all processes may be manually performed.
[0167] As described above, the present invention is not limited to the above-described embodiments
as they are and can be embodied by modifying the components without departing from
the gist of the present invention in the implementation stage. In addition, various
inventions can be formed by appropriately combining a plurality of components disclosed
in the above embodiments. For example, some components may be deleted from all the
components described in the embodiments. Furthermore, components in different embodiments
may be appropriately combined.
Reference Signs List
[0168]
- 1
- taxis analysis system
- 10, 10b
- processor
- 11
- container supply unit
- 111
- supply conveyor
- 112
- supply robot
- 12
- stationary table
- 13
- container take-out unit
- 131
- take-out robot
- 132
- container conveyance unit
- 1321
- arm
- 133
- lid removal unit
- 1331
- robot hand
- 134
- sensor
- 14
- control unit
- 15
- imaging unit
- 151
- support column
- 152
- base member
- 153
- light source
- 16
- storage
- 161
- image database
- 162
- inspection database
- 17
- analysis unit
- 21, 21b
- petri dish
- 22
- lid
- 3
- taxis analysis device
- 31
- camera control unit
- 32
- image processing unit
- 33
- analysis unit